Cloud-Aerosol Lidar And Infrared Pathfinder Satellite Observations Research Articles

Contribution of blowing-snow sublimation to the surface mass balance of Antarctica

Abstract. Blowing-snow sublimation is a key boundary layer process in polar regions and is the major ablation term in the surface mass balance (SMB) of the Antarctic ice sheet. This study updates the blowing-snow model in the Regional Atmospheric Climate Model (RACMO), version 2.3p3, incorporating blowing-snow sublimation into the prognostic equations for temperature and water vapour. These updates address numerical artefacts in the previous model version by replacing the uniformly discretised ice particle radius distribution, which limited the maximum ice particle radius to ≤ 50 µm, with a non-uniform distribution covering radii from 2 to 300 µm without additional computational overhead. The improved model is validated against meteorological observations from site D47 in Adélie Land, East Antarctica. The updates fix the numerical artefacts, successfully predicting the power-law variation in the blowing-snow flux with wind speed while improving the prediction of its magnitude. Additionally, a qualitative comparison with CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) satellite data shows that RACMO accurately forecasts the spatial pattern of monthly blowing-snow frequencies. The model also yields an average blowing-snow layer depth of 230±116 m at D47, matching typical satellite observation values. Results reveal that, without blowing snow, sublimation in Antarctica mainly occurs in summer (October–March), with minimal surface sublimation in winter (April–September). Introducing the blowing-snow model creates an additional sublimation mechanism primarily contributing in winter. From 2000–2012, model-integrated blowing-snow sublimation averaged 175±7 Gt yr−1, a 52 % increase from the previous version. Total sublimation, summing blowing-snow and surface sublimation, reached 234±10 Gt yr−1, 47 % higher than in simulations without the blowing-snow model. This increase leads to a 1.2 % reduction in the Antarctic ice sheet's integrated SMB. Additionally, changes in sublimation in coastal and lower escarpment zones underscore the importance of the model updates for Antarctic climatology.

Using space lidar to infer bubble cloud depth on a global scale

Visible and microwave satellite measurements can provide the global whitecap fraction. The bubble clouds are three-dimensional structures, and a space-based lidar can provide complementary observations of the bubble depth. Here, we use lidar measurements of the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite to quantify global bubble depth from the depolarization. The relationship between CALIPSO bubble depth and wind speed from the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) and AMSR2 is similar to a recently derived relationship based on buoy measurements. The CALIPSO-based bubble depth data show global distributions and seasonal variations consistent with the high wind speed (> 7 m/s) but with some variance. We also found similarities between the CALIPSO bubble depth and the whitecap fraction from AMSR2 and WindSat. Our findings support the use of spaceborne lidar measurements for advancing the understanding of the 3D bubble properties, and the ocean physics at high wind speeds.

Spaceborne lidar measurement of global cloud properties through machine learning

With a large footprint size, multiple scattering measurements of clouds from spaceborne lidar provide useful information about cloud physical properties, such as cloud optical depths and cloud droplet size, both during daytime and nighttime. A neural network algorithm, with a subset of cloud backscatter profiles of dual-polarization and dual-wavelength Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) lidar measurements during daytime as input variables and cloud physical properties derived from collocated Moderate Resolution Imaging Spectroradiometer (MODIS) multi-spectral measurements as output, is developed and evaluated with an independent subset of the collocated CALIPSO and MODIS measurements. The study suggests that with a receiver footprint size of 110 m, CALIPSO lidar measurements are sensitive to liquid-phase cloud optical depth variations from 0 to 25. A larger footprint size, thus more multiple scattering, is required for lidar to have sensitivities to all liquid-phase clouds. The technique can be applied to all 17 years of CALIPSO daytime and nighttime measurements and, thus, provides useful information about global distributions of cloud physical properties both during day and night.

Turbulent heat fluxes in the North Water Polynya and ice estimated based on ASRv2 data and their impact on cloud

The presence or absence of sea ice introduces a substantial perturbation to surface‒atmosphere energy exchanges. Comprehending the effect of varying sea ice cover on surface‒atmosphere interactions is an important consideration for understanding the Arctic climate system. The recurring North Water Polynya (NOW) serves as a natural laboratory for isolating cloud responses to a rapid, near-step perturbation in sea ice. In this study, we employed high-resolution Arctic System Reanalysis version 2 (ASRv2) data to estimate turbulent heat fluxes over the NOW and nearby sea ice (NSI) area between 2005/2006 and 2015/2016. The results indicate that the average turbulent heat fluxes in the polynya are about 87% and 86% higher than in the NSI area over the 10 years during the entire duration of the polynya and during polar night, respectively. Enhanced turbulent heat fluxes from the polynya tend to produce more low-level clouds. The relationship between the polynya and low cloud in winter was examined based on Cloud‒Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). The low-cloud fraction (0–2 km) was about 7–34% larger over the polynya than the NSI area, and the ice water content below 200 m was about 250%–413% higher over the former than the latter. The correlation between cloud fraction and turbulent heat fluxes in the polynya peaks around the altitude of 200–300 m. These results suggest that the NOW affects the Arctic boundary layer cloudiness and structure in wintertime. Furthermore, higher horizontal resolution reanalysis data can advance our understanding of the cloud-polynya response.

Assessing Aerosol Changes over Delhi using Satellite and Ground Measurement Data: Insights from a COVID-19 Lockdown Period

The tragic COVID-19 pandemic, while presenting numerous devastating consequences, has inadvertently provided a unique opportunity for studying air pollution. In this study, we specifically evaluate the spatiotemporal changes in aerosols before and during the COVID-19 lockdown from March to May 2020 over Northwest India, with a particular focus on two subregions in the vicinity of Delhi: Delhi-West and Delhi-East. The assessment was conducted using aerosol optical depth (AOD) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) mission, aerosol profiles from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) mission, and ground-based measurements of PM2.5 and PM10. Results demonstrated evident reductions in surface particulate matter and AOD during the lockdown. Approximately 40% of the contribution to the total AOD was from aerosols below 1 km. Different rates of change in AOD were observed for the two subregions across different lockdown phases, attributed to differences in emission sources: Delhi-East is more influenced by residential emissions, while Delhi-West is more affected by natural sources. The surface concentration and variabilities of PM2.5 and PM10 confirmed the differences between the two subregions, emphasizing the role of anthropogenic activities in PM2.5 emissions over the study area.

The Influences of Indian Monsoon Phases on Aerosol Distribution and Composition over India

This study investigates the impacts of summer monsoon activity on aerosols over the Indian region. We analyze the variability of aerosols during active and break monsoon phases, as well as strong and weak monsoon years, using data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). Our findings show a clear distinction in aerosol distribution between active and break phases. During active phases, the Aerosol Optical Depth (AOD) and aerosol extinction are lower across the Indian region, while break phases are associated with higher AOD and extinction. Furthermore, we observed a significant increase in AOD over Central India during strong monsoon years, compared to weak monsoon years. Utilizing the vertical feature mask (VFM) data from CALIPSO, we identified polluted dust and dusty marine aerosols as the dominant types during both active/break phases and strong/weak monsoon years. Notably, the contributions of these pollutants are significantly higher during break phases compared to during active phases. Our analysis also reveals a shift in the origin of these aerosol masses. During active phases, the majority originate from the Arabian Sea; in contrast, break phases are associated with a higher contribution from the African region.

Intensification mechanisms and moisture dynamics of super cyclonic storm ‘Amphan’ over the Bay of Bengal: Implications for aerosol re-distribution

The present research investigates the dynamics and underlying causes contributing to the exceptional intensity of Super Cyclonic Storm (SuCS) Amphan (16th to 21st May 2020) over the Bay of Bengal (BoB), as well as its impact on aerosol redistribution along the four cities of eastern coast and north-eastern India. Notably, the SuCS was formed during the first phase of the COVID-19 lockdown in India, giving it a unique aspect of study and analysis. Our analysis based on 30 years of climatology data from Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) reanalysis reveals ‘positive’ monthly anomalous winds (0.8 to 1.6 m/s) prevailed over the central BoB for May 2020. The present study further found the evolution of ‘barrier layer thickness’(BLT) leading up to landfall, noting a thickening trend from 8 to 3 days before landfall, contributing to maintaining warmer sea surface temperatures near the coast. Additionally, utilizing European Centre for Medium-Range Weather Forecasts (ECMWF), reanalysis version-5 (ERA-5) data, a mean positive sea surface temperature (SST) anomaly of 0.8 to 1 °C was observed ‘before’ cyclone period (10–15 May 2020) near the cyclogenesis point. A detailed examination of Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) vertical cross-section plots during the cyclone's intensification stage reveals the presence of high-altitude clouds composed primarily of ice crystals. Further, analysis also indicates that the cyclone transported Sea-salt PM2.5 aerosols from the ocean, dispersing them in the landfall region.The aerosol optical Depth (AOD) data obtained from the National Aeronautics and Space Administration's (NASA) ‘Clouds and the Earth's Radiant Energy System (CERES)’ mission and MERRA-2 were also analysed, revealing that the cyclone redistributed aerosols over the Bengal basin region (mainly over ‘Kolkata') and three other nearby cities along the track of the cyclone (i.e., Bhubaneswar (Odisha) Agartala (Tripura) and Shillong (Meghalaya) respectively).

Technical note: Retrieval of the supercooled liquid fraction in mixed-phase clouds from Himawari-8 observations

Abstract. The supercooled liquid fraction (SLF) in mixed-phase clouds (MPCs) is an essential variable of cloud microphysical processes and climate sensitivity. However, the SLF is currently calculated in spaceborne remote sensing only as the cloud phase–frequency ratio of adjacent pixels, which results in a loss of the original resolution in observations of cloud liquid or ice content within MPCs. Here, we present a novel method for retrieving the SLF in MPCs based on the differences in radiative properties of supercooled liquid droplets and ice particles at visible (VIS) and shortwave infrared (SWI) channels of the geostationary Himawari-8. Liquid and ice water paths are inferred by assuming that clouds are composed of only liquid or ice, with the real cloud water path (CWP) expressed as a combination of these two water paths (SLF and 1-SLF as coefficients), and the SLF is determined by referring to the CWP from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). The statistically relatively small cloud phase spatial inhomogeneity at a Himawari-8 pixel level indicates an optimal scene for cloud retrieval. The SLF results are comparable to global SLF distributions observed by active instruments, particularly for single-layered cloud systems. While accessing the method's feasibility, SLF averages are estimated between 74 % and 78 % in Southern Ocean (SO) stratocumulus across seasons, contrasting with a range of 29 % to 32 % in northeastern Asia. The former exhibits a minimum SLF around midday in summer and a maximum in winter, while the latter trend differs. This novel algorithm will be valuable for research to track the evolution of MPCs and constrain the related climate impact.

A Level 3 monthly gridded ice cloud dataset derived from 12 years of CALIOP measurements

Abstract. Clouds play important roles in weather, climate, and the global water cycle. The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) onboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) spacecraft has measured global vertical profiles of clouds and aerosols in the Earth’s atmosphere since June 2006. CALIOP provides vertically resolved information on cloud occurrence, thermodynamic phase, and properties. We describe version 1.0 of a monthly gridded ice cloud product derived from over 12 years of global, near-continuous CALIOP measurements. The primary contents are monthly vertically resolved histograms of ice cloud extinction coefficient and ice water content (IWC) retrievals. The CALIOP Level 3 Ice Cloud product is built from the CALIOP Version 4.20 Level 2 5 km Cloud Profile product that, relative to previous versions, features substantial improvements due to more accurate lidar backscatter calibration, better extinction coefficient retrievals, and a temperature-sensitive parameterization of IWC. The gridded ice cloud data are reported as histograms, which provides data users with the flexibility to compare CALIOP’s retrieved ice cloud properties with those from other instruments with different measurement sensitivities or retrieval capabilities. It is also convenient to aggregate monthly histograms for seasonal, annual, or decadal trend and climate analyses. This CALIOP gridded ice cloud product provides a unique characterization of the global and regional vertical distributions of optically thin ice clouds and deep convection cloud tops, and it should provide significant value for cloud research and model evaluation. A DOI has been issued for the product: https://doi.org/10.5067/CALIOP/CALIPSO/L3_ICE_CLOUD-STANDARD-V1-00 (Winker et al., 2018).

A near-global multiyear climate data record of the fine-mode and coarse-mode components of atmospheric pure dust

Abstract. A new four-dimensional, multiyear, and near-global climate data record of the fine-mode (submicrometer in terms of diameter) and coarse-mode (supermicrometer in terms of diameter) components of atmospheric pure dust is presented. The separation of the two modes of dust in detected atmospheric dust layers is based on a combination of (1) the total pure-dust product provided by the well-established European Space Agency (ESA) “LIdar climatology of Vertical Aerosol Structure” (LIVAS) database and (2) the coarse-mode component of pure dust provided by the first step of the two-step POlarization LIdar PHOtometer Networking (POLIPHON) technique, developed in the framework of the European Aerosol Research Lidar Network (EARLINET). Accordingly, the fine-mode component of pure dust is extracted as the residual between the LIVAS total pure dust and the coarse-mode component of pure dust. Intermediate steps involve the implementation of regionally dependent lidar-derived lidar ratio values and AErosol RObotic NETwork (AERONET)-based climatological extinction-to-volume conversion factors, facilitating conversion of dust backscatter into extinction and subsequently extinction into mass concentration. The decoupling scheme is applied to observations from the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) at 532 nm. The final products consist of the fine mode and coarse mode of atmospheric pure dust, quality-assured profiles of backscatter coefficient at 532 nm, extinction coefficient at 532 nm, and mass concentration for each of the two components. The datasets are established primarily with the original L2 horizontal (5 km) and vertical (60 m) resolution of the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) along the CALIPSO orbit path and secondly in averaged profiles of seasonal–temporal resolution, 1° × 1° spatial resolution, and the original vertical resolution of CALIPSO, focusing on the latitudinal band extending between 70° S and 70° N and covering more than 15 years of Earth observations (June 2006–December 2021). The quality of the CALIPSO-based fine-mode and coarse-mode dust products is assessed through the use of AERONET fine-mode and coarse-mode aerosol optical thickness (AOT) interpolated to 532 nm and the AERosol properties – Dust (AER-D) campaign airborne in situ particle size distributions (PSDs) as reference datasets during atmospheric conditions characterized by dust presence. The near-global fine-mode and coarse-mode pure-dust climate data record is considered unique with respect to a wide range of potential applications, including climatological, time series, and trend analysis over extensive geographical domains and temporal periods, validation of atmospheric dust models and reanalysis datasets, assimilation activities, and investigation of the role of airborne dust in radiation and air quality.

Application of multiplatform remote sensing data over East Asia Ocean: aerosol characteristics and aerosol types.

It is important to explore the characteristics and rules of atmospheric aerosol in the East Asian Sea for monitoring and evaluating atmospheric environmental quality. Based on Aerosol Robot Network (AERONET), Visible Infrared Imaging Radiometer (VIIRS), and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) data, the temporal and spatial variation characteristics and differences of aerosol parameters and types in the East Asian Sea were studied by using figure classification method (FIGCM), aerosol optical depth (AOD)440-Angstrom exponent (AE)440-870 method (AA1M), and AOD550-AE490-670 method (AA2M). The results show that the seasonal variation trend of aerosol characteristics and types is obvious in East Asia Sea. AOD, volume concentration (Cv), and aerosol effective radius (reff) in the Bohai-Yellow Sea and the Sea of Japan in autumn are lower than those in other seasons, and the occurrence frequency of ocean-type aerosols is high. Different from the Bohai-Yellow Sea and Sea of Japan, human activities in winter, summer, and autumn seriously affect the air quality in the East China Sea and South China Sea. Especially at the Taipei CWB site, from aerosol parameters and high biomass burning/urban industrial (BB/UI) aerosol, human activity is an important factor for high pollution at the Taipei CWB site. Aerosol types of AA1M, FIGCM, AA2M, and CALIPSO were compared at Anmyon and Yonsei University sites in the Bohai-Yellow Sea in March 2020. The results show that aerosol types based on threshold classification methods generally have higher mixed aerosol results, and the marine (MA) results of AA1M, FIGCM, and AA2M are close to the clean marine aerosol results of CALIPSO. Comparing the results of AA 2M and CALIPSO on a spatial scale, it is found that the clean marine aerosol proportion identified by CALIPSO (0.38, 0.48, 0.82) is consistent with the MA proportion identified by AA 2M (0.43, 0.46, 0.97) in the East China Sea, South China Sea, and Western Pacific Ocean.

An iterative algorithm to simultaneously retrieve aerosol extinction and effective radius profiles using CALIOP

Abstract. The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on board the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite has been widely used in climate and environment studies to obtain the vertical profiles of atmospheric aerosols. To retrieve the vertical profile of aerosol extinction, the CALIOP algorithm assumes column-averaged lidar ratios based on a clustering of aerosol optical properties measured at surface stations. On one hand, these lidar ratio assumptions may not be appropriate or representative at certain locations. One the other hand, the two-wavelength design of CALIOP has the potential to constrain aerosol size information, which has not been considered in the operational algorithm. In this study, we present a modified inversion algorithm to simultaneously retrieve aerosol extinction and effective radius profiles using two-wavelength elastic lidars such as CALIOP. Specifically, a lookup table is built to relate the lidar ratio with the Ångström exponent calculated using aerosol extinction at the two wavelengths, and the lidar ratio is then determined iteratively without a priori assumptions. The retrieved two-wavelength extinction at each layer is then converted to the particle effective radius assuming a lognormal distribution. The algorithm is tested on synthetic data, Raman lidar measurements and then finally the real CALIOP backscatter measurements. Results show improvements over the CALIPSO operational algorithm by comparing with ground-based Raman lidar profiles.

Validation of Satellite‐Based Cloud Phase Distributions Using Global‐Scale In Situ Airborne Observations

AbstractUnderstanding distributions of cloud thermodynamic phases is important for accurately representing cloud radiative effects and cloud feedback in a changing climate. Satellite‐based cloud phase data have been frequently used to compare with climate models, yet few studies validated them against in situ observations at a near‐global scale. This study aims to validate three satellite‐based cloud phase products using a compositive in situ airborne data set developed from 11 flight campaigns. Latitudinal‐altitudinal cross sections of cloud phase occurrence frequencies are examined. The Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) show the most similar vertical profiles of ice phase frequencies compared with in situ observations. The CloudSat data overestimate mixed‐phase frequencies up to 15 km but provide better sampling through cloud layers than lidar data. The DARDAR (raDAR/liDAR) data show a sharp transition between ice and liquid phase and overestimate ice phase frequency at most altitudes and latitudes. The satellite data are further evaluated for various latitudes, longitudes, and seasons, which show higher ice phase frequency in the extratropics in their respective wintertime and smaller impacts from longitudinal variations. The Southern Ocean shows a thicker mixing region where liquid and ice phases have similar frequencies compared with tropics and Northern Hemisphere (NH) extratropics. Two comparison methods with different spatiotemporal windows show similar results, which demonstrates the statistical robustness of these comparisons. Overall, this study develops a near global‐scale in situ observational data set to assess the accuracy of satellite‐based cloud phase products and investigates the key factors affecting the distributions of cloud phases.

CALIPSO Observed Low Clouds Over the Subtropical Northeast Pacific: Summer Climatology and Interannual Variability

AbstractThis study examines the spatial distribution and temporal variations of low‐cloud top over the subtropical northeast Pacific (NEP), using observations from the Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). A comparison between CALIPSO observations and in‐situ soundings reveals a distinct bimodal distribution of low‐cloud tops, characterized by peaks near the inversion base and transition layer, corresponding to shallow cumulus clouds below the stratocumulus deck and boundary‐layer decoupling phenomena. Climatologically, while traversing along a great circle from Los Angeles to Honolulu, the frequency of low cloud occurrence experiences a gradual reduction from 80% to 30%. Meanwhile, cloud top height increases from 0.6 to 1.6 km, and surface roughness varies from 50 to 300 m. This study marks the first presentation of long‐term characteristics of low clouds over a vast, remote area, expanding beyond discrete field campaign observations. Accurately characterizing the marine atmospheric boundary layer (MABL) including its depth and degree of decoupling, enables further investigation into the interannual variations of low clouds, using 14 years of CALIPSO observations. Significant interannual variability in areal fraction and vertical bimodality of low clouds emerges downstream of the anomalously cold water; increased cloud cover with weakened bimodality is associated with a shallow weakly decoupled MABL. This research emphasizes the need to consider the downstream effects in studying low cloud‐sea surface temperature feedback within climate models.

Seasonal vertical distributions of diurnal variation of ice cloud frequency by CATS measurements over a global region (51°S-51°N)

Ice clouds can strongly affect the radiation budget through the reflection (absorption) of solar shortwave (longwave) radiation in the Earth-atmosphere system. Unlike water clouds, ice clouds present a longer lifetime in the upper troposphere. Therefore, the vertical patterns of diurnal variation of ice clouds are of very importance to understand climate change in the globe. The present paper investigates the diurnal variation of ice cloud frequency (ICF) from March 2015 to October 2017 over the global scale (51 ° S and 51 ° N) by CATS (Cloud-Aerosol Transport System) LiDAR onboard the International Space Station (ISS) and CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) LiDAR measurements. Our results suggest that: (1) ICF derived from the CATS and CALIPSO LiDAR presents the similar geographical variations. (2) The vertical distribution of ICF in land area over the North Hemisphere (NH) is found larger than in the South Hemisphere (SH) likely due to the more dust aerosols as ice nuclei to influence ice cloud formation over the NH. (3) ICF at nighttime (00:00–06:00 and 18:00–23:00) exhibits higher value than daytime (06:00–18:00), especially in high altitude (more than 12 km) ice clouds in the tropics. (4) The number of ice cloud samples is higher in spring and winter compared to summer and autumn, and the highest amount of ice cloud samples in spring(winter) occurs during nighttime(daytime) for most hours. These findings provide significant insights that may help improving the ice cloud's representation in climate models.

Three-dimensional reconstruction of aerosols based on spectral radiance matching

This paper evaluates a three-dimensional scene construction algorithm that assigns CALIPSO-observed profiles to receiving pixels in MODIS imagery through spectral radiance matching (SRM), so that a limited number of vertically resolved aerosol observations can be expanded into a regionally continuous three-dimensional aerosol structure. The SRM algorithm was tested using moderate resolution imaging spectro-radiometer (MODIS) and cloud-aerosol lidar and infrared pathfinder satellite observation (CALIPSO) data for the period of April 10–25, 2015. First, the spectral radiance channel and the surface reflectance channel were selected for combination tests to select the best channel combination 01-04-07-26 for the application of SRM algorithm in the field of aerosol three-dimensional reconstruction. The average aerosol matching rate for this channel combination can reach 90.57%, 81.64%, 78.6%, 74.12%, and 65.96% at extended distances of 5, 20, 30, 50, and 100 km, respectively. In addition, the combination of the average correct match rate and the reconstructed aerosol structure revealed that the most suitable extension distance is up to 100 km. Then, for the reconstruction profile validation, lidar sites under four weather conditions (clean sky, aerosol loading, thin clouds, and thick clouds) were selected for validation. The comparison results reveal that the average relative errors are about 30%, 60%, 30%–60%, and 70% for these four conditions, respectively. Overall, the average relative error of the reconstructed profiles within 100 km of the orbital track of CALIPSO (except under thick cloud conditions) is less than 60%, which is within a reasonable error envelop. There are also some limitations that can be improved later by adding more constraints: 1) it is difficult to reconstruct some short-time, small-scale aerosol or cloud features; 2) it is difficult to reconstruct some hierarchical structures under thick clouds due to signal attenuation caused by thick clouds; 3) there is an underestimation of the attenuated backscatter coefficient under clouds. Finally, for aerosol optical depth (AOD), the SRM algorithm largely underestimates AOD. The reconstructed AOD is in good agreement with aerosol robotic network (AERONET), with R2=0.8231 after removal of outliers.

A global gridded dataset for cloud vertical structure from combined CloudSat and CALIPSO observations

Abstract. The vertical structure of clouds has a profound effect on the global energy budget, the global circulation, and the atmospheric hydrological cycle. The CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) missions have taken complementary, colocated observations of cloud vertical structure for over a decade. However, no globally gridded dataset is available to the public for the full length of this unique combined data record. Here we present the 3S-GEOPROF-COMB product (Bertrand et al. 2023, https://doi.org/10.5281/zenodo.8057791), a globally gridded (level 3S) community data product summarizing geometrical profiles (GEOPROF) of hydrometeor occurrence from combined (COMB) CloudSat and CALIPSO data. Our product is calculated from the latest release (R05) of per-orbit (level-2) combined cloud mask profiles. We process a set of cloud cover, vertical cloud fraction, and sampling variables at 2.5, 5, and 10° spatial resolutions and monthly and seasonal temporal resolutions. We address the 2011 reduction in CloudSat data collection with Daylight-Only Operations (DO-Op) mode by subsampling pre-2011 data to mimic DO-Op collection patterns, thereby allowing users to evaluate the impact of the reduced sampling on their analyses. We evaluate our data product against CloudSat-only and CALIPSO-only global-gridded data products as well as four comparable surface-based sites, underscoring the added value of the combined product. Interest in the product is anticipated for the study of cloud processes, cloud–climate interactions, and as a candidate baseline climate data record for comparison to follow-up satellite missions, among other uses.

Validation of initial observation from the first spaceborne high-spectral-resolution lidar with a ground-based lidar network

Abstract. On 16 April 2022, China successfully launched the world's first spaceborne high-spectral-resolution lidar (HSRL), which is called the Aerosol and Carbon Detection Lidar (ACDL), on board the Atmospheric Environment Monitoring Satellite known as Daqi-1 (DQ-1). The ACDL is expected to precisely detect the three-dimensional distribution of aerosol and cloud globally with high spatial–temporal resolutions. To assess the performance of the newly launched satellite lidar, the ACDL-retrieved observations were compared with ground-based lidar measurements of atmospheric aerosol and cloud over northwest China from May to July 2022 using the Belt and Road lidar network (BR-lidarnet) initiated by Lanzhou University in China and the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) lidar observations. A total of six cases in the daytime and nighttime, including clear days, dust events, and cloudy conditions, were selected for further analysis. Moreover, profiles of the total attenuated backscatter coefficient (TABC) and the volume depolarization ratio (VDR) at 532 nm measured by the ACDL, the CALIPSO lidar, and ground-based lidar are compared in detail. Comparison is made between the 532 nm extinction coefficient and lidar ratio obtained from ACDL HSRL retrieval and the Raman retrieval results obtained from BR-lidarnet. The achieved results revealed that the ACDL observations were in good agreement with the ground-based lidar measurements during dust events with a relative deviation of about −10.5 ± 25.4 % for the TABC and −6.0 ± 38.5 % for the VDR. Additionally, the heights of the cloud top and bottom from these two measurements were well matched and comparable. Compared with the observation of CALIPSO, the ACDL also shows high consistency. This study proves that the ACDL provides reliable observations of aerosol and cloud in the presence of various climatic conditions, which helps to further evaluate the impacts of aerosol on climate and the environment, as well as on the ecosystem in the future.

The Tibetan Plateau space-based tropospheric aerosol climatology: 2007–2020

Abstract. A comprehensive and robust dataset of tropospheric aerosol properties is important for understanding the effects of aerosol–radiation feedback on the climate system and reducing the uncertainties of climate models. The “Third Pole” of Earth (Tibetan Plateau, TP) is highly challenging for obtaining long-term in situ aerosol data due to its harsh environmental conditions. Here, we provide the more reliable new vertical aerosol index (AI) parameter from the spaceborne-based lidar CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) on board CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) for daytime and nighttime to investigate the aerosol's climatology over the TP region during 2007–2020. The calculated vertical AI was derived from the aerosol extinction coefficient (EC), which was rigorously quality-checked and validated for passive satellite sensors (MODIS) and ground-based lidar measurements. Generally, our results demonstrated that there was agreement of the AI dataset with the CALIOP and ground-based lidar. In addition, the results showed that, after removing the low-reliability aerosol target signal, the optimized data can obtain the aerosol characteristics with higher reliability. The data also reveal the patterns and concentrations of high-altitude vertical structure characteristics of the tropospheric aerosol over the TP. They will also help to update and make up the observational aerosol data in the TP. We encourage climate modelling groups to consider new analyses of the AI vertical patterns, comparing the more accurate datasets, with the potential to increase our understanding of the aerosol–cloud interaction (ACI) and aerosol–radiation interaction (ARI) and their climate effects. Data described in this work are available at https://doi.org/10.11888/Atmos.tpdc.300614 (Huang, 2023).

Lessons Learned from the Updated GEWEX Cloud Assessment Database

AbstractSince the first Global Energy and Water Exchanges cloud assessment a decade ago, existing cloud property retrievals have been revised and new retrievals have been developed. The new global long-term cloud datasets show, in general, similar results to those of the previous assessment. A notable exception is the reduced cloud amount provided by the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Science Team, resulting from an improved aerosol–cloud distinction. Height, opacity and thermodynamic phase determine the radiative effect of clouds. Their distributions as well as relative occurrences of cloud types distinguished by height and optical depth are discussed. The similar results of the two assessments indicate that further improvement, in particular on vertical cloud layering, can only be achieved by combining complementary information. We suggest such combination methods to estimate the amount of all clouds within the atmospheric column, including those hidden by clouds aloft. The results compare well with those from CloudSat-CALIPSO radar–lidar geometrical profiles as well as with results from the International Satellite Cloud Climatology Project (ISCCP) corrected by the cloud vertical layer model, which is used for the computation of the ISCCP-derived radiative fluxes. Furthermore, we highlight studies on cloud monitoring using the information from the histograms of the database and give guidelines for: (1) the use of satellite-retrieved cloud properties in climate studies and climate model evaluation and (2) improved retrieval strategies.